{"id":"https://openalex.org/W4295308409","doi":"https://doi.org/10.1109/tnnls.2022.3202700","title":"Graph-Based Dissimilarity Measurement for Cluster Analysis of Any-Type-Attributed Data","display_name":"Graph-Based Dissimilarity Measurement for Cluster Analysis of Any-Type-Attributed Data","publication_year":2022,"publication_date":"2022-09-12","ids":{"openalex":"https://openalex.org/W4295308409","doi":"https://doi.org/10.1109/tnnls.2022.3202700","pmid":"https://pubmed.ncbi.nlm.nih.gov/36094993"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3202700","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3202700","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tnnls.2022.3202700","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100329232","display_name":"Yiqun Zhang","orcid":"https://orcid.org/0000-0002-0328-987X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0328-987X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038516431","display_name":"Yiu\u2010ming Cheung","orcid":"https://orcid.org/0000-0001-7629-4648"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yiu-Ming Cheung","raw_affiliation_strings":["Department of Computer Science, Hong Kong Baptist University, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7629-4648","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.393,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95430984,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"34","issue":"9","first_page":"6530","last_page":"6544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.8128331899642944},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7062365412712097},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6399924755096436},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6039363741874695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5671831369400024},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5319530963897705},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5162723064422607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34516972303390503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3383503556251526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3245968222618103},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2766517996788025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23489099740982056},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07805955410003662}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8128331899642944},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7062365412712097},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6399924755096436},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6039363741874695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5671831369400024},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5319530963897705},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5162723064422607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34516972303390503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3383503556251526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3245968222618103},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2766517996788025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23489099740982056},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07805955410003662},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3202700","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3202700","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36094993","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36094993","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":{"id":"doi:10.1109/tnnls.2022.3202700","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3202700","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G365222834","display_name":null,"funder_award_id":"62102097","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3675971206","display_name":null,"funder_award_id":"2022A1515011592","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4787607161","display_name":null,"funder_award_id":"RC-FNRA-IG/18-19/SCI/03","funder_id":"https://openalex.org/F4320320955","funder_display_name":"Hong Kong Baptist University"},{"id":"https://openalex.org/G6515857316","display_name":null,"funder_award_id":"N_HKBU214/21","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320955","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W114704759","https://openalex.org/W1523794535","https://openalex.org/W1565746575","https://openalex.org/W1605406256","https://openalex.org/W1647729745","https://openalex.org/W1992419399","https://openalex.org/W1996426270","https://openalex.org/W2010140249","https://openalex.org/W2019044299","https://openalex.org/W2020344074","https://openalex.org/W2047878524","https://openalex.org/W2132149726","https://openalex.org/W2143668817","https://openalex.org/W2143687373","https://openalex.org/W2148425841","https://openalex.org/W2149230623","https://openalex.org/W2149620660","https://openalex.org/W2185136252","https://openalex.org/W2187089797","https://openalex.org/W2338257905","https://openalex.org/W2345750043","https://openalex.org/W2473552888","https://openalex.org/W2600906272","https://openalex.org/W2740337541","https://openalex.org/W2793385194","https://openalex.org/W2811024573","https://openalex.org/W2811389973","https://openalex.org/W2887997457","https://openalex.org/W2895388200","https://openalex.org/W2909504023","https://openalex.org/W2925162041","https://openalex.org/W2951429788","https://openalex.org/W2997152122","https://openalex.org/W3017786722","https://openalex.org/W3043922872","https://openalex.org/W3107721972","https://openalex.org/W3128396846","https://openalex.org/W3161522974","https://openalex.org/W3164473340","https://openalex.org/W3187834303","https://openalex.org/W4244030505","https://openalex.org/W4285601133","https://openalex.org/W4302768905","https://openalex.org/W6604645885","https://openalex.org/W6636975626","https://openalex.org/W6681822384","https://openalex.org/W6704569244","https://openalex.org/W6732085715","https://openalex.org/W6754278344","https://openalex.org/W6790575088","https://openalex.org/W6799137738"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2133382151","https://openalex.org/W2153339597","https://openalex.org/W1528412344"],"abstract_inverted_index":{"Heterogeneous":[0],"attribute":[1,161],"data":[2,21,63],"composed":[3,199],"of":[4,9,17,110,133,166,197,200,204],"attributes":[5,67,73,82,89,96,144],"with":[6,65,76,84,91,180,217],"different":[7,78],"types":[8],"values":[10,70,162],"are":[11,74,83,90],"quite":[12],"common":[13],"in":[14,45,215],"a":[15,29,42,53,126,152,173],"variety":[16],"real-world":[18],"applications.":[19],"As":[20],"annotation":[22],"is":[23,52,154,191],"usually":[24],"expensive,":[25],"clustering":[26,48,177],"has":[27],"provided":[28],"promising":[30],"way":[31],"for":[32,130,149],"processing":[33],"unlabeled":[34],"data,":[35],"where":[36],"the":[37,47,60,69,107,115,119,139,142,158,164,167,188],"adopted":[38],"similarity":[39,61],"measure":[40],"plays":[41],"key":[43],"role":[44],"determining":[46],"accuracy.":[49],"However,":[50],"it":[51],"very":[54,77],"challenging":[55],"task":[56],"to":[57,106,193],"appropriately":[58],"define":[59],"between":[62,160],"objects":[64],"heterogeneous":[66,72,120,143],"because":[68],"from":[71],"generally":[75],"characteristics.":[79],"Specifically,":[80],"numerical":[81],"quantitative":[85],"values,":[86],"while":[87],"categorical":[88,95],"qualitative":[92],"values.":[93,112],"Furthermore,":[94],"can":[97],"be":[98],"categorized":[99],"into":[100],"nominal":[101],"and":[102,145,207],"ordinal":[103,208],"ones":[104],"according":[105],"order":[108],"information":[109],"their":[111],"To":[113],"circumvent":[114],"awkward":[116],"gap":[117],"among":[118,141],"attributes,":[121],"this":[122,181],"article":[123],"will":[124],"propose":[125],"new":[127,174],"dissimilarity":[128],"metric":[129,153],"cluster":[131,195],"analysis":[132,196],"such":[134],"data.":[135],"We":[136],"first":[137],"study":[138],"connections":[140],"build":[146],"graph":[147,168],"representations":[148],"them.":[150],"Then,":[151],"proposed,":[155],"which":[156],"computes":[157],"dissimilarities":[159],"under":[163],"guidance":[165],"structures.":[169],"Finally,":[170],"we":[171],"develop":[172],"k":[175],"-means-type":[176],"algorithm":[178],"associated":[179],"proposed":[182,189],"metric.":[183],"It":[184],"turns":[185],"out":[186],"that":[187],"method":[190],"competent":[192],"perform":[194],"datasets":[198],"an":[201],"arbitrary":[202],"combination":[203],"numerical,":[205],"nominal,":[206],"attributes.":[209],"Experimental":[210],"results":[211],"show":[212],"its":[213,218],"efficacy":[214],"comparison":[216],"counterparts.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
